EFFICIENT FAULT LOCATION IN UNDERGROUND DISTRIBUTION SYSTEMS THROUGH OPTIMUM-PATH FOREST

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

An Intelligent System for Petroleum Well Drilling Cutting Analysis

Cutting analysis is a important and crucial task task to detect and prevent problems during the petroleum well drilling process. Several studies have been developed for drilling inspection, but none of them takes care about analysing the generated cutting at the vibrating shale shakers. Here we proposed a system to analyse the cutting's concentration at the vibrating shale shakers, which can indicate problems during the petroleum well drilling process, such that the collapse of the well borehole walls. Cutting's images are acquired and sent to the data analysis module, which has as the main goal to extract features and to classify frames according to one of three previously classes of cutting's volume. A collection of supervised classifiers were applied in order to allow comparisons about their accuracy and efficiency. We used the Optimum-Path Forest (OPF), Artificial Neural Network using Multi layer Perceptrons (ANN-MLP), Support Vector Machines (SVM) and a Bayesian Classifier (BC) for this task. The first one outperformed all the remaining classifiers. Recall that we are also the first to introduce the OPF classifier in this field of knowledge. Very good results show the robustness of the proposed system, which can be also integrated with other commonly system (Mud-Logging) in order to improve the last one's efficiency.

Adaptive filter feature identification for structural health monitoring in an aeronautical panel

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Identificação e comparação entre controle preditivo com modelo não linear e PI sintonizados com PSO em sistema de separação gravitacional de águia-óleo

The separation methods are reduced applications as a result of the operational costs, the low output and the long time to separate the uids. But, these treatment methods are important because of the need for extraction of unwanted contaminants in the oil production. The water and the concentration of oil in water should be minimal (around 40 to 20 ppm) in order to take it to the sea. Because of the need of primary treatment, the objective of this project is to study and implement algorithms for identification of polynomial NARX (Nonlinear Auto-Regressive with Exogenous Input) models in closed loop, implement a structural identification, and compare strategies using PI control and updated on-line NARX predictive models on a combination of three-phase separator in series with three hydro cyclones batteries. The main goal of this project is to: obtain an optimized process of phase separation that will regulate the system, even in the presence of oil gushes; Show that it is possible to get optimized tunings for controllers analyzing the mesh as a whole, and evaluate and compare the strategies of PI and predictive control applied to the process. To accomplish these goals a simulator was used to represent the three phase separator and hydro cyclones. Algorithms were developed for system identification (NARX) using RLS(Recursive Least Square), along with methods for structure models detection. Predictive Control Algorithms were also implemented with NARX model updated on-line, and optimization algorithms using PSO (Particle Swarm Optimization). This project ends with a comparison of results obtained from the use of PI and predictive controllers (both with optimal state through the algorithm of cloud particles) in the simulated system. Thus, concluding that the performed optimizations make the system less sensitive to external perturbations and when optimized, the two controllers show similar results with the assessment of predictive control somewhat less sensitive to disturbances

Association between IGF-I, IGF-IR and GHRH gene polymorphisms and growth and carcass traits in beef cattle

Molecular biology techniques are of help in genetic improvement since they permit the identification, mapping and analysis of polymorphisms of genes encoding proteins that act on metabolic pathways involved in economically interesting traits. The somatotrophic axis, which essentially consists of growth hormone releasing hormone (GHRH), growth hormone (GH), insulin-like growth factors I and II (IGF-I and IGF-II), and their associated binding proteins and receptors (GHRHR, GHR, IGF-IR and IGF-IIR), plays a key role in the metabolism and physiology of mammalian growth. The objectives of the present study were to estimate the allele and genotype frequencies of the IGF-I/SnaBI, IGF-IR/TaqI and GHRH/HaeIII gene polymorphisms in different genetic groups of beef cattle and to determine associations between these polymorphisms and growth and carcass traits. For this purpose, genotyping was performed on 79 Nellore animals, 30 Canchim (5/8 Charolais+3/8 Zebu) animals and 275 crossbred cattle originating from the crosses of Simmental (n=30) and Angus (n=245) sires with Nellore females. In the association studies, traits of interest were analyzed using the GLM procedure of SAS and least square means of the genotypes were compared by the Tukey test. Associations of IGF-I/SnaBI genotypes with body weight and subcutaneous backfat were significant (p < 0.05), and nearly significant for longissimus dorsi area (p=0.06), with the 1313 genotype being favorable compared to the AB genotype. No significant associations were observed between this polymorphism and weight gain or carcass yield (P > 0.05). The IGF-IR/TaqI and GHRH/HaeIII polymorphisms showed no association with production traits. (c) 2004 Elsevier B.V All rights reserved.

Bovine gene polymorphisms related to fat deposition and meat tenderness

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Growth and carcass traits associated with GH1/Alu I and POU1F1/Hinf I gene polymorphisms in Zebu and crossbred beef cattle

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Petroleum well drilling monitoring through cutting image analysis and artificial intelligence techniques

Petroleum well drilling monitoring has become an important tool for detecting and preventing problems during the well drilling process. In this paper, we propose to assist the drilling process by analyzing the cutting images at the vibrating shake shaker, in which different concentrations of cuttings can indicate possible problems, such as the collapse of the well borehole walls. In such a way, we present here an innovative computer vision system composed by a real time cutting volume estimator addressed by support vector regression. As far we know, we are the first to propose the petroleum well drilling monitoring by cutting image analysis. We also applied a collection of supervised classifiers for cutting volume classification. (C) 2010 Elsevier Ltd. All rights reserved.

Multivariate calibrations in gas chromatographic profiles for prediction of several physicochemical parameters of Brazilian commercial gasoline

Several Brazilian commercial gasoline physicochemical parameters, such as relative density, distillation curve (temperatures related to 10%, 50% and 90% of distilled volume, final boiling point and residue), octane numbers (motor and research octane number and anti-knock index), hydrocarbon compositions (olefins, aromatics and saturates) and anhydrous ethanol and benzene content was predicted from chromatographic profiles obtained by flame ionization detection (GC-FID) and using partial least square regression (PLS). GC-FID is a technique intensively used for fuel quality control due to its convenience, speed, accuracy and simplicity and its profiles are much easier to interpret and understand than results produced by other techniques. Another advantage is that it permits association with multivariate methods of analysis, such as PLS. The chromatogram profiles were recorded and used to deploy PLS models for each property. The standard error of prediction (SEP) has been the main parameter considered to select the "best model". Most of GC-FID-PLS results, when compared to those obtained by the Brazilian Government Petroleum, Natural Gas and Biofuels Agency - ANP Regulation 309 specification methods, were very good. In general, all PLS models developed in these work provide unbiased predictions with lows standard error of prediction and percentage average relative error (below 11.5 and 5.0, respectively). (C) 2007 Elsevier B.V. All rights reserved.

Influência do modelo de análise estatística e da forma das parcelas experimentais na seleção de clones de Eucalyptus spp.

Foram avaliadas três formas de parcelas experimentais (retangular, uma linha - linear e parcela de uma árvore - STP) em testes clonais de Eucalyptus spp, utilizando-se três experimentos, cada um com 18 clones. Foram usados três modelos de análise (mínimos quadrados ordinários - ANOVA tradicional, modelos mistos com fator clone fixo ou com fator clone aleatório - REML/BLUP). Os dois primeiros modelos apresentaram resultados similares. Com REML/BLUP houve estreitamento das predições em relação às amplitudes obtidas com as médias, e essa redução foi proporcionalmente maior com parcelas retangulares e STP. O ordenamento dos clones também foi similar com esses dois tipos de parcelas. É provável que com parcelas STP haja um balanço compensatório das alocompetições, pois se pode trabalhar com maior número de repetições e menor custo. Portanto, com parcelas STP haverá economia de recursos e sem prejuízos para o Programa de Melhoramento Florestal.

Estimativa de ocorrência de precipitação em áreas agrícolas utilizando floresta de caminhos ótimos

As condições meteorológicas são determinantes para a produção agrícola; a precipitação, em particular, pode ser citada como a mais influente por sua relação direta com o balanço hídrico. Neste sentido, modelos agrometeorológicos, os quais se baseiam nas respostas das culturas às condições meteorológicas, vêm sendo cada vez mais utilizados para a estimativa de rendimentos agrícolas. Devido às dificuldades de obtenção de dados para abastecer tais modelos, métodos de estimativa de precipitação utilizando imagens dos canais espectrais dos satélites meteorológicos têm sido empregados para esta finalidade. O presente trabalho tem por objetivo utilizar o classificador de padrões floresta de caminhos ótimos para correlacionar informações disponíveis no canal espectral infravermelho do satélite meteorológico GOES-12 com a refletividade obtida pelo radar do IPMET/UNESP localizado no município de Bauru, visando o desenvolvimento de um modelo para a detecção de ocorrência de precipitação. Nos experimentos foram comparados quatro algoritmos de classificação: redes neurais artificiais (ANN), k-vizinhos mais próximos (k-NN), máquinas de vetores de suporte (SVM) e floresta de caminhos ótimos (OPF). Este último obteve melhor resultado, tanto em eficiência quanto em precisão.

Association of GH and IGF-1 polymorphisms with growth traits in a synthetic beef cattle breed

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Estimativas de parâmetros genéticos e fenotípicos e análise de componentes principais para características de crescimento na raça Canchim

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Application of a meshless method in electromagnetics

An improved meshless method is presented with an emphasis on the detailed description of this new computational technique and its numerical implementations by investigating the usefulness of a commonly neglected parameter in this paper. Two approaches to enforce essential boundary conditions are also thoroughly investigated. Numerical tests on a mathematical function is carried out as a means of validating the proposed method. It will be seen that the proposed method is more robust than the conventional ones. Applications in solving electromagnetic problems are also presented.

Avaliação do peso à desmama e do ganho médio de peso de bezerros cruzados, no estado do Mato Grosso do Sul

O objetivo deste trabalho foi comparar o desempenho de bezerros mestiços de diferentes grupos genéticos até a desmama. Informações de 3631 bezerros F1 filhos de vacas Nelore com touros Aberdeen Angus, Brangus, Brangus (pelagem vermelha), Canchim, Gelbvieh, Nelore e Simental foram usadas (Grupo 1). Foram usadas também informações de 1896 bezerros de fêmeas Nelore com touros das raças supracitadas e de fêmeas F1 retrocruzadas com touros Gelbvieh e Nelore (Grupo 2). Os pesos à desmama foram ajustados aos 230 dias (PD230) e aos 240 dias (PD240), para os grupos 1 e 2, respectivamente, e o ganho médio diário até a desmama (GMD), para ambos os grupos, foi determinado. O modelo matemático usado nas análises pelo método de quadrados mínimos incluiu os efeitos fixos de grupo contemporâneo (GC), grupo genético do bezerro (GG) e idade do bezerro e idade da vaca. GC e GG influenciaram as características estudadas em ambos os grupos. A idade do bezerro não influiu significativamente no PD230 e GMD no Grupo 1, mas no Grupo 2 foi significativa para PD240 e GMD. A idade da vaca ao parto influenciou as características estudadas tanto no Grupo 1 como no Grupo 2. Os animais cruzados foram superiores aos puros Nelore em ambos os grupos. Foi obtido, a partir do Grupo 2, um terceiro conjunto de dados, Grupo 3, contendo os produtos do retrocruzamento de fêmeas F1, Nelore-Gelbvieh, com touros Gelbvieh e Nelore, contendo 722 informações de PD240 e GMD. Nesse arquivo foram estimados os efeitos aditivos direto e materno e heterótico individual. Apenas o efeito heterótico individual foi significativo.